This disclosure is directed to computers and computer applications, and more particularly to computer-implemented methods and systems for generating personalized video interjections based on a learner model and a learning objective and inserting the personalized video interjections into a video at locations in the video to maximize learning.
Computer based adaptive learning solutions have been shown to be effective. However, automated tutoring systems can be much more effective if the learning is interactive and participative. Videos can be quite an engaging medium for knowledge delivery, but effective learning requires the video to have two way interaction. However, interactive engagement does not directly translate to learning, as the learner often can skip over content that they do not understand and still remain engaged since the rest of the content is sufficient for them to understand the overall context.
Current video-based knowledge delivery solutions are one-way, even though they contain significant useful knowledge. The few solutions that include two-way interactions are not personalized to a learner. Instead, typical adaptive learning solutions have specific predetermined interjections that are used equally for all learners without an understanding of the learner's specific learning objective or learning level.